[Pkg-exppsy-pymvpa-dev] pymvpa and spatially related features

[Yaroslav Halchenko]

Hi Satra,

well --  in 0.5 (under development) you can add arbitrary number of
descriptors for features to be kept in .fa (feature attribute)
collections.  So you can make one to keep flags (or just descriptors)
for curvature/thickness. or one for neghborhood (we already embed 3D
coordinates so we could perform searchlight).

Unfortunately, indeed, we don't have yet any classifier which
would take advantage of such groupping automagically.  At some point
I've asked SMLR author about accounting for features to be groupped
while doing feature elimination, but that subproject didn't pick up.
Also there exists DrSVM (THE DOUBLY REGULARIZED SUPPORT VECTOR MACHINE)
which could take advantage of groupping but authors didn't reply to my
in wries and I didn't have enough motivation to implement it from
scratch.

What specific use for those did you have in mind?

On Thu, 06 May 2010, Satrajit Ghosh wrote:

>    hi,
>    i have a set of features that share geometrical/spatial properties. is
>    there a way i can tell pymvpa that these features are tied together?
>    for example, i might get curvature and cortical thickness from a single
>    vertex as features, but currently i don't encode the fact that these
>    two features are related. the ds is just a nsubj x nfeat matrix.
>    and related to this question, are there specific classifiers that can
>    take advantage of this relation?
>    and to extend it beyond simple grouping based on location, can i
>    include neighborhood relations on surfaces  or to generalize
>    (connectivity on graphs).
>    cheers,
>    satra

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